Sometimes models are written in programming languages, but this is a long and expensive process. Mathematical packages can be used for modeling, but experience shows that they usually lack many engineering tools. It is optimal to use a simulation environment.
In our course, we chose . The labs and demos you will encounter in the course should be run as projects in the Stratum-2000 environment.
The model, made taking into account the possibility of its modernization, of course, has disadvantages, for example, low speed of code execution. But there are also undeniable advantages. The model structure, connections, elements, subsystems are visible and saved. You can always go back and redo something. A trace in the history of model design is preserved (but when the model is debugged, it makes sense to remove service information from the project). In the end, the model that is handed over to the customer can be designed in the form of a specialized automated workstation (AWS), written in a programming language, in which attention is mainly paid to the interface, speed parameters and other consumer properties that are important for customer. The workstation is, of course, an expensive thing, so it is released only when the customer has fully tested the project in the modeling environment, made all the comments and undertakes not to change his requirements anymore.
Modeling is an engineering science, a problem-solving technology. This remark is very important. Since technology is a way to achieve a result with a quality known in advance and guaranteed costs and deadlines, then modeling as a discipline:
- studies ways to solve problems, that is, it is an engineering science;
- is a universal tool that guarantees the solution of any problems, regardless of the subject area.
Subjects related to modeling are: programming, mathematics, operations research.
Programming because the model is often implemented on an artificial medium (plasticine, water, bricks, mathematical expressions), and the computer is one of the most universal media of information and, moreover, active (simulates plasticine, water, bricks, calculates mathematical expressions, etc.). Programming is a way of expressing an algorithm in a language form. Algorithm is one of the ways of representing (reflecting) a thought, process, phenomenon in an artificial computing environment, which is a computer (von Neumann architecture). The specificity of the algorithm is to reflect the sequence of actions. Modeling can use programming if the object being modeled is easy to describe in terms of its behavior. If it is easier to describe the properties of an object, then it is difficult to use programming. If the simulation environment is not built on the basis of von Neumann architecture, programming is practically useless.
What is the difference between an algorithm and a model?
An algorithm is a process of solving a problem by implementing a sequence of steps, while a model is a set of potential properties of an object. If you pose a question to the model and add additional conditions in the form of initial data (connection with other objects, initial conditions, restrictions), then it can be resolved by the researcher regarding unknowns. The process of solving a problem can be represented by an algorithm (but other solution methods are also known). In general, examples of algorithms in nature are unknown; they are the product of the human brain, the mind, capable of establishing a plan. Actually, the algorithm is a plan, developed into a sequence of actions. It is necessary to distinguish between the behavior of objects associated with natural causes and the providence of the mind, controlling the course of movement, predicting the result on the basis of knowledge and choosing the appropriate behavior.
model + question + additional conditions = task.
Mathematics is a science that provides the possibility of calculating models that can be reduced to a standard (canonical) form. The science of finding solutions to analytical models (analysis) using formal transformations.
Operations research a discipline that implements methods for studying models from the point of view of finding the best control actions on models (synthesis). Mostly deals with analytical models. Helps make decisions using built models.
Design the process of creating an object and its model; modeling a way to evaluate the design result; There is no modeling without design.
Related disciplines for modeling include electrical engineering, economics, biology, geography, and others in the sense that they use modeling methods to study their own applied object (for example, a landscape model, an electrical circuit model, a cash flow model, etc.).
As an example, let's look at how a pattern can be detected and then described.
Let’s say that we need to solve the “Cutting Problem”, that is, we need to predict how many cuts in the form of straight lines will be required to divide the figure (Fig. 1.16) into a given number of pieces (for example, it is enough that the figure is convex).
Let's try to solve this problem manually.
From Fig. 1.16 it is clear that with 0 cuts 1 piece is formed, with 1 cut 2 pieces are formed, with two 4, with three 7, with four 11. Can you now tell in advance how many cuts will be required to form, for example, 821 pieces ? In my opinion, no! Why are you having trouble? You do not know the pattern K = f(P) , Where K number of pieces, P number of cuts. How to spot a pattern?
Let's make a table connecting the known numbers of pieces and cuts.
The pattern is not yet clear. Therefore, let's look at the differences between individual experiments, let's see how the result of one experiment differs from another. Having understood the difference, we will find a way to move from one result to another, that is, a law connecting K And P .
A certain pattern has already emerged, hasn’t it?
Let's calculate the second differences.
Now everything is simple. Function f called generating function. If it is linear, then the first differences are equal. If it is quadratic, then the second differences are equal to each other. And so on.
Function f There is a special case of Newton's formula:
Odds a , b , c , d , e for our quadratic functions f are in the first cells of the rows of experimental table 1.5.
So, there is a pattern, and it is this:
K = a + b · p + c · p · ( p 1)/2 = 1 + p + p · ( p 1)/2 = 0.5 · p 2 + 0.5 p + 1 .
Now that the pattern has been determined, we can solve the inverse problem and answer the question posed: how many cuts must be made to get 821 pieces? K = 821 , K= 0.5 · p 2 + 0.5 p + 1 , p = ?
Solving a quadratic equation 821 = 0.5 · p 2 + 0.5 p + 1 , we find the roots: p = 40 .
Let's summarize (pay attention to this!).
We couldn't guess the solution right away. Conducting the experiment turned out to be difficult. I had to build a model, that is, find a pattern between the variables. The model was obtained in the form of an equation. By adding a question to the equation and an equation reflecting a known condition, a problem was formed. Since the problem turned out to be of a typical type (canonical), it was solved using one of the well-known methods. Therefore, the problem was solved.
And it is also very important to note that the model reflects cause-and-effect relationships. There is indeed a strong connection between the variables of the constructed model. A change in one variable entails a change in another. We said earlier that “the model plays a system-forming and meaning-forming role in scientific knowledge, it allows us to understand the phenomenon, the structure of the object under study, and establish the connection between cause and effect.” This means that the model allows us to determine the causes of phenomena and the nature of the interaction of its components. The model relates causes and effects through laws, that is, variables are related to each other through equations or expressions.
But!!! Mathematics itself does not make it possible to derive any laws or models from the results of experiments, as it may seem after the example just considered. Mathematics is only a way of studying an object, a phenomenon, and, moreover, one of several possible ways of thinking. There is also, for example, a religious method or a method that artists use, an emotional-intuitive one, with the help of these methods they also learn about the world, nature, people, themselves.
So, the hypothesis about the connection between variables A and B must be introduced by the researcher himself, from the outside, in addition. How does a person do this? It’s easy to advise introducing a hypothesis, but how to teach this, explain this action, and therefore, again, how to formalize it? We will show this in detail in the future course “Modeling Artificial Intelligence Systems”.
But why this must be done from the outside, separately, additionally and in addition, we will explain now. This reasoning bears the name of Gödel, who proved the incompleteness theorem: it is impossible to prove the correctness of a certain theory (model) within the framework of the same theory (model). Look again at Fig. 1.12. The higher level model transforms equivalent lower level model from one species to another. Or it generates a lower-level model based on its equivalent description. But she cannot transform herself. The model builds the model. And this pyramid of models (theories) is endless.
In the meantime, in order to “not get blown up by nonsense,” you need to be on your guard and check everything with common sense. Let's give an example, an old well-known joke from the folklore of physicists.
Simulation method the most promising research method requires a certain level of mathematical training from the psychologist. Here, mental phenomena are studied on the basis of an approximate image of reality - its model. The model makes it possible to focus the psychologist’s attention only on the main, most significant features of the psyche. A model is an authorized representative of the object being studied (mental phenomenon, thinking process, etc.). Of course, it is better to immediately get a holistic understanding of the phenomenon being studied. But this is usually impossible due to the complexity of psychological objects.
The model is related to its original by a similarity relationship.
Cognition of the original from the standpoint of psychology occurs through complex processes of mental reflection. The original and its psychic reflection are related like an object and its shadow. Complete cognition of an object is carried out sequentially, asymptotically, through a long chain of cognition of approximate images. These approximate images are models of the cognizable original.
The need for modeling arises in psychology when:
- the systemic complexity of an object is an insurmountable obstacle to creating its holistic image at all levels of detail;
- rapid study of a psychological object is required to the detriment of the detail of the original;
- mental processes with a high level of uncertainty are subject to study and the patterns to which they obey are unknown;
- optimization of the object under study is required by varying input factors.
Modeling tasks:
- description and analysis of mental phenomena at various levels of their structural organization;
- forecasting the development of mental phenomena;
- identification of mental phenomena, i.e. establishing their similarities and differences;
- optimization of conditions for the occurrence of mental processes.
Briefly about the classification of models in psychology. There are object and symbolic models. Subject ones have a physical nature and, in turn, are divided into natural and artificial. Natural models are based on representatives of living nature: people, animals, insects. Let us remember man's faithful friend, the dog, which served as a model for studying the functioning of human physiological mechanisms. Artificial models are based on elements of “second nature” created by human labor. As an example, we can cite F. Gorbov’s homeostat and N. Obozov’s cybernometer, which are used to study group activity.
Sign models are created on the basis of a system of signs of very different nature. This:
- alphanumeric models, where letters and numbers act as signs (such, for example, is the model for regulating joint activities of N. N. Obozov);
- models of special symbols (for example, algorithmic models of the activities of A. I. Gubinsky and G. V. Sukhodolsky in engineering psychology or musical notation for an orchestral piece of music, which contains all the necessary elements that synchronize the complex joint work of performers);
- graphic models that describe an object in the form of circles and lines of communication between them (the former can express, for example, the states of a psychological object, the latter - possible transitions from one state to another);
- mathematical models that use a diverse language of mathematical symbols and have their own classification scheme;
- cybernetic models are built on the basis of the theory of automatic control and simulation systems, information theory, etc.
In this paper, we propose to analyze the topic of modeling in computer science in as much detail as possible. This section is of great importance for training future specialists in the field of information technology.
To solve any problem (industrial or scientific), computer science uses the following chain:
It is worth paying special attention to the concept of “model”. Without this link, solving the problem will not be possible. Why is the model used and what is meant by this term? We'll talk about this in the next section.
Model
Modeling in computer science is the creation of an image of any real-life object that reflects all the essential features and properties. A model for solving a problem is necessary, since it is, in fact, used in the solution process.
In the school computer science course, the topic of modeling begins to be studied in the sixth grade. At the very beginning, children need to be introduced to the concept of a model. What it is?
- Simplified object similarity;
- A smaller copy of a real object;
- Scheme of a phenomenon or process;
- Image of a phenomenon or process;
- Description of a phenomenon or process;
- Physical analogue of an object;
- Information analogue;
- A placeholder object that reflects the properties of the real object, and so on.
A model is a very broad concept, as has already become clear from the above. It is important to note that all models are usually divided into groups:
- material;
- perfect.
A material model is understood as an object based on a real-life object. It could be any body or process. This group is usually divided into two more types:
- physical;
- analog.
This classification is conditional, because it is very difficult to draw a clear boundary between these two subspecies.
The ideal model is even more difficult to characterize. It is related to:
- thinking;
- imagination;
- perception.
This includes works of art (theater, painting, literature, and so on).
Modeling Goals
Modeling in computer science is a very important stage, as it serves many purposes. Now we invite you to get to know them.
First of all, modeling helps to understand the world around us. From time immemorial, people accumulated the knowledge they acquired and passed it on to their descendants. Thus, a model of our planet (globe) appeared.
In past centuries, modeling was carried out on non-existent objects that are now firmly entrenched in our lives (an umbrella, a mill, and so on). Currently, modeling is aimed at:
- identifying the consequences of any process (increasing the cost of travel or recycling chemical waste underground);
- ensuring the effectiveness of decisions made.
Modeling tasks
Information model
Now let's talk about another type of models studied in a school computer science course. Computer modeling, which every future IT specialist needs to master, includes the process of implementing an information model using computer tools. But what is this, an information model?
It is a whole list of information about an object. What does this model describe and what useful information does it contain:
- properties of the modeled object;
- his condition;
- connections with the outside world;
- relationships with external objects.
What can serve as an information model:
- verbal description;
- text;
- drawing;
- table;
- scheme;
- drawing;
- formula and so on.
A distinctive feature of the information model is that it cannot be touched, tasted, and so on. It does not carry a material embodiment, as it is presented in the form of information.
Systematic approach to creating a model
In which grade of the school curriculum is modeling studied? 9th grade computer science introduces students to this topic in more detail. It is in this class that the child learns about the systematic approach to modeling. We suggest we talk about this in a little more detail.
Let's start with the concept of “system”. It is a group of interconnected elements that work together to accomplish a given task. To build a model, a systems approach is often used, since an object is considered as a system operating in a certain environment. If any complex object is modeled, then the system is usually divided into smaller parts - subsystems.
Purpose of use
Now we will look at the goals of modeling (computer science, grade 11). Earlier it was said that all models are divided into certain types and classes, but the boundaries between them are arbitrary. There are several characteristics by which models are usually classified: purpose, area of knowledge, time factor, method of presentation.
As for goals, it is customary to distinguish the following types:
- educational;
- experienced;
- imitation;
- gaming;
- scientific and technical.
The first type includes educational materials. The second is reduced or enlarged copies of real objects (a model of a structure, an airplane wing, and so on). allows you to predict the outcome of an event. Simulation modeling is often used in medicine and the social sphere. For example, does the model help to understand how people will react to a particular reform? Before performing a serious operation on a person for an organ transplant, many experiments were carried out. In other words, a simulation model allows you to solve a problem by trial and error. The game model is a kind of economic, business or military game. Using this model, you can predict the behavior of an object in different situations. A scientific and technical model is used to study any process or phenomenon (a device simulating a lightning discharge, a model of the movement of the planets of the solar system, and so on).
Field of knowledge
In which class are students introduced to modeling in more detail? 9th grade computer science focuses on preparing its students for exams for admission to higher education institutions. Since the Unified State Exam and State Examination tickets contain questions on modeling, it is now necessary to consider this topic in as much detail as possible. So, how does classification by area of knowledge occur? Based on this feature, the following types are distinguished:
- biological (for example, artificially caused diseases in animals, genetic disorders, malignant neoplasms);
- behavior of the company, model of market price formation, and so on);
- historical (family tree, models of historical events, model of the Roman army, etc.);
- sociological (model of personal interest, behavior of bankers when adapting to new economic conditions) and so on.
Time factor
According to this characteristic, two types of models are distinguished:
- dynamic;
- static.
Judging by the name alone, it is not difficult to guess that the first type reflects the functioning, development and change of an object over time. Static, on the contrary, is capable of describing an object at a specific point in time. This type is sometimes called structural, since the model reflects the structure and parameters of the object, that is, it provides a snapshot of information about it.
Examples are:
- a set of formulas reflecting the movement of the planets of the solar system;
- graph of air temperature changes;
- video recording of a volcanic eruption and so on.
Examples of a statistical model are:
- list of planets of the solar system;
- area map and so on.
Presentation method
To begin with, it is very important to say that all models have a form and shape, they are always made of something, somehow represented or described. According to this criterion, it is accepted as follows:
- material;
- intangible.
The first type includes material copies of existing objects. You can touch them, smell them, and so on. They reflect the external or internal properties and actions of an object. Why are material models needed? They are used for the experimental method of cognition (experimental method).
We also addressed intangible models earlier. They use a theoretical method of cognition. Such models are usually called ideal or abstract. This category is divided into several more subtypes: imaginary models and informational ones.
Information models provide a list of various information about an object. The information model can be tables, pictures, verbal descriptions, diagrams, and so on. Why is this model called intangible? The whole point is that you cannot touch it, since it has no material embodiment. Among information models, a distinction is made between iconic and visual.
An imaginary model is one of the creative processes that takes place in a person’s imagination, which precedes the creation of a material object.
Modeling stages
The 9th grade computer science topic “Modeling and Formalization” has a lot of weight. It is a must-learn. In grades 9-11, the teacher is required to introduce students to the stages of creating models. This is what we will do now. So, the following stages of modeling are distinguished:
- meaningful statement of the problem;
- mathematical formulation of the problem;
- development using computers;
- operation of the model;
- getting the result.
It is important to note that when studying everything that surrounds us, processes of modeling and formalization are used. Computer science is a subject dedicated to modern methods of studying and solving problems. Consequently, the emphasis is on models that can be implemented using a computer. Particular attention in this topic should be paid to the development of a solution algorithm using electronic computers.
Relationships between objects
Now let's talk a little about connections between objects. There are three types in total:
- one to one (such a connection is indicated by a one-way arrow in one direction or the other);
- one to many (multiple relationships are indicated by a double arrow);
- many to many (this relationship is indicated by a double arrow).
It is important to note that connections can be conditional or unconditional. An unconditional link involves using every instance of an object. And in the conditional only individual elements are involved.
Modeling is the replacement of one object (original) with another (model) and fixation or study of the properties of the original by studying the properties of the model.
Model is a representation of an object, system or concept (idea) in some form that is different from the form of its real existence.
The benefits of modeling can only be achieved if the following fairly obvious conditions are met:
The model adequately reflects the properties of the original that are significant from the point of view of the purpose of the study;
The model allows you to eliminate the problems inherent in taking measurements on real objects.
Approaches (methods) to modeling.
1) Classic (inductive) examines the system by moving from the particular to the general, i.e. The system model is built from the bottom up and synthesized by merging the element models of the component systems, developed separately.
2) System. Transition from general to specific. The model is based on the purpose of the study. It is from this that they start when creating a model. The goal is what we want to know about the object.
Let's consider the basic principles of modeling.
1) The principle of information sufficiency. It is necessary to collect information that will provide a sufficient level of information.
2) The principle of feasibility. The model must ensure achievement of the goal within a realistically specified time.
3) Aggregation principle. A complex system consists of subsystems (units), for which You can build independent models and combine them into a common model. The model turns out to be flexible. When changing the goal, a number of component modules can be used. The model is feasible if
And 
.
Classification of modeling methods.
1) By the nature of the processes being studied
Deterministic - during the functioning of the modeled object, random factors are not taken into account (everything is predetermined).
Stochastic – the impact of various factors on existing real systems is taken into account
2) Based on development over time
Static – the behavior of an object is described at a certain time
Dynamic – for a certain period of time
3) According to the presentation of information in the model
Discrete - if events leading to changes in states occur at a certain point in time.
Continuous, discrete-continuous.
4) According to the form of presentation of the modeling object
Mental- if the modeling object does not exist, or exists outside the conditions for its physical creation.
A) Symbolic. Creating a logical object that replaces the real one.
B) Mathematical
Analytical. An object is described using functional relationships, followed by an attempt to obtain an explicit solution.
Imitation. The algorithm that describes the functioning of the system reproduces the process of the object’s operation over time. This method is also called statistical, because statistics of simulated phenomena are collected. (based on the Monte Carlo method - static test method)
B) Visual
Real- there is an object.
A) Natural. The experiment is carried out on the modeling object itself. The most common form is testing.
B) Physical. Research is carried out on a special basis. Installations, processes in the cat. They have a physical similarity with processes in real objects.
The analytical model can be studied using the following methods:
A) analytical: an attempt to obtain solutions explicitly (general);
b) numerical: obtain a numerical solution under given initial conditions (partial nature of the solutions);
V) quality: Without having an explicit solution, you can find the properties of the solution in explicit form.
In simulation modeling, the algorithm that describes the functioning of the system reproduces the process of the object’s operation over time. This method is also called statistical, because statistics of simulated phenomena are collected. (based on the Monte Carlo method)
The concepts of “model”, “simulation”, various approaches to the classification of models. Modeling stages
Model (modelium)– about Latin measure, image, manner, etc.
Model- this is a new object, different from the original one, which has properties essential for modeling purposes and, within the framework of these goals, replaces the original object (the object is the original)
Or we can say in other words: a model is a simplified representation of a real object, process or phenomenon.
Conclusion. The model is needed in order to:
Understand how a specific object is structured - what are its structure, basic properties, laws of development and interaction with the outside world;
Learn to manage an object or process and determine the best management methods for given goals and criteria (optimization);
Predict direct and indirect consequences of implementing specified methods and forms of impact on the object;
Classification of models.
Signs by which models are classified:
1. Area of use.
2. Taking into account the time factor and area of use.
3. According to the method of presentation.
4. Branch of knowledge (biological, historical, sociological, etc.).
5. Area of use
Educational: visual aids, training programs, various simulators;
Experienced: a ship model is tested in a pool to determine the stability of the ship when rocking;
Scientific and technical: an electron accelerator, a device that simulates a lightning discharge, a stand for testing a TV;
Gaming: military, economic, sports, business games;
Imitation: the experiment is either repeated many times in order to study and evaluate the consequences of any actions on a real situation, or is carried out simultaneously with many other similar objects, but placed under different conditions).
2. Taking into account the time factor and area of use
Static model - it’s like a one-time slice through an object.
Example: You came to the dental clinic for an oral examination. The doctor examined me and wrote down all the information on the card. Entries in the card that give a picture of the state of the oral cavity at a given time (number of milk, permanent, filled, extracted teeth) will be a statistical model.
Dynamic model allows you to see changes in an object over time.
An example is the same card of a schoolchild, which reflects the changes occurring in his teeth over a certain point in time.
3. Classification by method of presentation
The first two large groups: material and informational. The names of these groups seem to indicate what the models are made of.
Material models can otherwise be called objective, physical. They reproduce the geometric and physical properties of the original and always have a real embodiment.
Kids toys. From them the child gets his first impression of the world around him. A two-year-old child plays with a teddy bear. When, years later, a child sees a real bear in a zoo, he will easily recognize it.
School textbooks, physical and chemical experiments. They simulate processes, such as the reaction between hydrogen and oxygen. This experience is accompanied by a deafening bang. The model confirms the consequences of the emergence of an “explosive mixture” of harmless and widespread substances in nature.
Maps when studying history or geography, diagrams of the solar system and the starry sky in astronomy lessons and much more.
Conclusion. Material models implement a material (touch, smell, see, hear) approach to the study of an object, phenomenon or process.
Information models cannot be touched or seen with your own eyes; they have no material embodiment, because they are built only on information. This modeling method is based on an information approach to studying the surrounding reality.
Information models - a set of information that characterizes the properties and states of an object, process, phenomenon, as well as the relationship with the outside world.
Information characterizing an object or process can have different volumes and forms of presentation, and be expressed in different ways. This diversity is as limitless as the capabilities of each person and his imagination. Information models include symbolic and verbal.
Iconic model - an information model expressed by special signs, i.e., by means of any formal language.
Iconic models are all around us. These are drawings, texts, graphs and diagrams.
According to the method of implementation, iconic models can be divided into computer and non-computer ones.
Computer model - a model implemented by means of a software environment.
Verbal (from the Latin “verbalis” - oral) model - an information model in mental or spoken form.
These are models obtained as a result of reflection and inference. They can remain mental or be expressed verbally. An example of such a model would be our behavior when crossing the street.
The process of building a model is called modeling; in other words, modeling is the process of studying the structure and properties of the original using a model.
Planetariums" href="/text/category/planetarii/" rel="bookmark">planetarium, in architecture - building models, in aircraft manufacturing - aircraft models, etc.
Ideal modeling is fundamentally different from subject (material) modeling.
Perfect modeling is not based on a material analogy of an object and a model, but on an ideal, conceivable analogy.
Iconic modeling is modeling that uses symbolic transformations of any kind as models: diagrams, graphs, drawings, formulas, sets of symbols.
Mathematical modeling is modeling in which the study of an object is carried out through a model formulated in the language of mathematics: description and study of Newton's laws of mechanics using mathematical formulas.
The modeling process consists of the following stages:
The main task of the modeling process is to select the most adequate model to the original and transfer the research results to the original. There are quite general methods and methods of modeling.
Before building a model of an object (phenomenon, process), it is necessary to identify its constituent elements and the connections between them (conduct a system analysis) and “translate” (display) the resulting structure into some predetermined form - to formalize the information.
Formalization is the process of identifying and translating the internal structure of an object, phenomenon or process into a specific information structure - form.
Formalization is the reduction of essential properties and characteristics of a modeling object in the selected form (to the selected formal language).
Modeling stages
Before taking on any work, you need to clearly imagine the starting point and each point of the activity, as well as its approximate stages. The same can be said about modeling. The starting point here is a prototype. It can be an existing or designed object or process. The final stage of modeling is making a decision based on knowledge about the object.
The chain looks like this.
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STAGE I. STAGE TASKS.
A task is a problem that needs to be solved. At the stage of problem formulation, it is necessary to reflect three main points: description of the problem, determination of modeling goals and analysis of the object or process.
Description of the task
The task is formulated in ordinary language, and the description should be clear. The main thing here is to define the modeling object and understand what the result should be.
Purpose of modeling
1) knowledge of the surrounding world
2) creation of objects with given properties (determined by posing the problem “how to do so that...”.
3) determining the consequences of impact on the object and making the right decision. The purpose of modeling problems like “what will happen if...” (what will happen if you increase the fare for transport, or what will happen if you bury nuclear waste in such and such an area?)
Object Analysis
At this stage, the modeled object and its main properties are clearly identified, what it consists of, and what connections exist between them.
A simple example of subordinate object connections is parsing a sentence. First, the main members (subject, predicate) are highlighted, then the minor members related to the main ones, then the words related to the secondary ones, etc.
STAGE II. MODEL DEVELOPMENT
1. Information model
At this stage, the properties, states, actions and other characteristics of elementary objects are clarified in any form: verbally, in the form of diagrams, tables. An idea is formed about the elementary objects that make up the original object, i.e., an information model.
Models must reflect the most essential features, properties, states and relationships of objects in the objective world. They provide complete information about the object.
2. Iconic model
Before starting the modeling process, a person makes preliminary sketches of drawings or diagrams on paper, derives calculation formulas, i.e., compiles an information model in one or another symbolic form, which can be either computer or non-computer.
3. Computer model
A computer model is a model implemented using a software environment.
There are many software packages that allow you to conduct research (modeling) of information models. Each software environment has its own tools and allows you to work with certain types of information objects.
The person already knows what the model will be and uses the computer to give it an iconic shape. For example, graphical environments are used to build geometric models and diagrams, and a text editor environment is used for verbal or tabular descriptions.
STAGE III. COMPUTER EXPERIMENT
With the development of computer technology, a new unique research method has emerged - a computer experiment. A computer experiment includes a sequence of working with a model, a set of targeted user actions on a computer model.
STAGE IV ANALYSIS OF MODELING RESULTS
The ultimate goal of modeling is making a decision, which should be made on the basis of a comprehensive analysis of the results obtained. This stage is decisive - either you continue the research or finish it. Perhaps you know the expected result, then you need to compare the obtained and expected results. If there is a match, you will be able to make a decision.